Remove the feeds module

content/node.a8753236-c6ec-4eab-88c0-cf1939cf0333.json

@@ -87,14 +87,5 @@
             "processed": "\n          <p>I recently listened to a podcast that discussed Elon Musk and quoted something like, \"If 20% of attempts aren't failing, you aren't taking enough risk\".<\/p>\n\n<p>In a software context, I'm not advocating that one in five production releases should fail, but I like trying new ideas and approaches.<\/p>\n\n<p>If you're releasing small changes regularly or practising continuous deployment, changes are easy to revert if there's a problem or the smaller the deployment and the more recently the code was written, then it should be easier to resolve the issue and \"fix forward\" instead of rolling back.<\/p>\n\n<p>Using feature flags lets you quickly turn off a feature flag while investigating and resolving the issue without needing another deployment.<\/p>\n\n<p>If you have an appropriate plan to follow in the case of an issue, that mitigates the risk and minimises the impact of a potential issue - making it quicker to resolve and restore the service.<\/p>\n\n<p>Two of the DORA metrics refer to failure rate and restoration time:<\/p>\n\n<ul>\n<li>Deployment frequency<\/li>\n<li>Lead time for changes<\/li>\n<li>Change failure rate<\/li>\n<li>Time to restore service<\/li>\n<\/ul>\n\n<p>Then, it depends on your organisation's tolerance for risk and what's acceptable.<\/p>\n\n<p>But, the more frequent the releases, the lower the failure rate and the quicker it will be to restore the service if there is an issue.<\/p>\n\n        ",
             "summary": null
         }
-    ],
-    "feeds_item": [
-        {
-            "imported": "1970-01-01T00:32:50+00:00",
-            "guid": null,
-            "hash": "2a2b5c587a4d8d90d889a8595926719e",
-            "target_type": "feeds_feed",
-            "target_uuid": "90c85284-7ca8-4074-9178-97ff8384fe76"
-        }
     ]
 }